摘要
阐述了近年来国内外出现的Reactive Tree、GAP-tree、Multi-Scale Hilbert R-tree、Multiple R-tree等6种矢量数据多尺度空间索引方法,对它们的优缺点作了较为详细的评述,为索引方法的选择和应用提供了一定的理论依据。最后,给出了对后续研究有指导性的结论,提出了高维索引、优化索引等多尺度空间索引方法未来的研究方向。
The problem about multi-representations of spatial data is one of the hot topics in modern GIS. We pointed out that a.ll kinds of published solutions could be concluded as three kinds of type techniques： explicit storage of multi-scale vector data, multi-scale spatial index, multi-scale vector data storage structure. Because there is more fertile soil to seed multi-scale spatial index method, we expatiated six kinds of multi-scale spatial index meth- od, such as Reactive Tree, GAP-tree, Multi-Scale Hilbert R-tree, Multiple R-tree, and fol- lowed their development in recent years. According to our research experiments, we dis- cussed their advantages and disadvantages, and provided some academic bases for their chosen and applications. Finally, we drawn some conclusions to guide the research on multiscale spatial methods, and proposed the further research on multi-dimension index and opti- mized index.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2009年第5期597-601,共5页
Geomatics and Information Science of Wuhan University
基金
国家863计划资助项目(2007AA120401
2006AA120106)
国家自然科学基金资助项目(40401047)
关键词
矢量数据
多尺度
空间索引
vector data
multi-scale
spatial index
